Work with cutting edge technology, making the world a safer and more secure place.
DroneShield (ASX : DRO) offers an opportunity to solve some of the world's most challenging technical problems in the Electronic Warfare, Artificial Intelligence and Machine Learning, RF sensing, Sensor Fusion and distributed systems.
Working with high profile customers across militaries, government agencies, airports, critical infrastructure, law enforcement and many others.
With an approximately $1bn market capitalisation and having raised approximately $250m in 2024 alone, DroneShield is undergoing hypergrowth stage, fuelled by rapidly increasing use of drones for nefarious applications, from battlefield, to terrorism, to contraband delivery and commercial espionage.
This role is in the DroneShield Sydney headquarters in Pyrmont, Sydney.
There are approximately 200 staff based in the 4,000sqm facility today, scheduled to grow to approximately 300 staff by end of 2026.
Overseas on the ground presence includes Virginia (USA), Denmark, Germany and Dubai, as well as distributors in over 70 countries globally.
About the role As the Data Engineering Team Lead, you will spearhead the Data Engineering efforts within our organization, driving the team responsible for building and maintaining the data infrastructure that supports our Algorithms and AI teams.
Your leadership will play a pivotal role in improving our Detect and Defeat capabilities in the fast-paced, cutting-edge field of drone technology.
This role demands strategic oversight and hands-on expertise in creating scalable, efficient, and secure data systems, helping us derive meaningful insights, solve technical challenges, and deliver superior solutions to our clients.
You will lead a team of talented data engineers, fostering a culture of innovation and growth while ensuring smooth, high-performance data operations.
Your efforts will be essential to the success and continued growth of our business as we navigate the evolving landscape of drone technology and AI-driven solutions.
Responsibilities, Duties and Expectations Lead the design, development, and maintenance of robust, scalable data processing systems, particularly with a focus on embedded sensors and large-scale raw data sources (e.g., IQ, radar, lidar, or video).
Oversee and drive innovation in automating manual processes, improving data pipelines, and redesigning infrastructure for scalability and improved efficiency.
Design and deploy secure, scalable, and self-hosted data infrastructure, ensuring it aligns with business needs and industry standards.
Collaborate with cross-functional teams (e.g., AI, Algorithms, Product Development) to understand data needs and deliver solutions that support key business objectives.
Provide technical leadership and mentorship to junior engineers, fostering a culture of continuous learning and development.
Develop tools and systems for monitoring, analyzing, and optimizing the performance of data infrastructure.
Lead efforts in developing and deploying machine learning models in production environments, ensuring high reliability and efficiency.
Coordinate and manage field data collection activities.
Lead the design, implementation, maintenance, and improvement of field data collection hardware, software, and processes.
Stay updated on the latest trends and advancements in data engineering, machine learning, and MLOps, applying these insights to drive continuous improvement.
Qualifications, Experience and Skills Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
5+ years of experience in data engineering, with at least 2+ years of leadership or team management experience.
Proven experience working with Big Data, ideally with raw or sensor data (e.g., IQ, radar, lidar, video).
Expertise in designing, building, and maintaining scalable data pipelines and workflow management tools (e.g., Dagster, DBT, or similar).
Extensive experience with both relational (SQL) and NoSQL databases.
Proficiency in Python and SQL is essential; experience with GoLang or C / C++ is a strong advantage.
Experience with data pipeline orchestration, automation, and optimizing infrastructure for performance.
Knowledge of deploying machine learning models and working with machine learning pipelines (MLOps).
Strong communication and leadership skills, with demonstrated success in mentoring and guiding junior engineers.
Digital Signal Processing (DSP) or RF telecommunications experience is desirable but not essential.
Previous exposure to drone technology, hobby drones, or RF emitter technology is advantageous.
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